I have, for a while, wanted to revisit the theory of Connectivism and deepen my understanding of its principles. Actually, I want to leverage the principles in my professional work.

I don’t know how consistent I will be in this study effort, but I’ll give it my best.

Today I found on Twitter the October 2015 edition of the International Journal of Instructional Technology and Distance Learning. I started studying the first article, Understanding Knowledge Network, Learning, and Connectivism, by AlDahdouh, A., Osório, A. J., and Caires, S.

Following are core concepts of Connectivism laid out by AlDahdouh et. al. (listed as far as I have studied their article and sources):

Connectivism does not try to build on any previous theoretical framework. but instead calls for a new framework.

Connectivism is a theory for the information age.

Connectivism acknowledges that two things change rapidly in modern learning environments: tool development and curriculum development.

Connectivism defines learning as what learners can reach in the network. It assumes knowledge as a network.

A network is a set of nodes connected by relationships.

A node is any object that can be connected (i.e., in a network).

There are three node types: neural, internal, and external.

A relationship is a link between two objects. These relationships can be graded, can tie to one another, and have directional properties with different characteristics.

A node can connect to itself.

A pattern is a set of connections appearing together as a single whole. The pattern is one of the most important concepts in Connectivism.

At the neural level, information is held in a connected set of neurons and not in a single neuron.

The node itself is a network (at all levels).

At the conceptual level, nodes are ideas and thoughts that help humans interpret the world (e.g., liquids). These concepts connect because of their “similar to” relationships.

“Two things that are relevantly similar become connected in the mind. This connection or association in turn allows knowledge about one to be inferred of the other.” Downes, 2007. In other words, concepts can become black boxes.

The external network has a diversity of node types.

Connectivism is built on Actor-Network Theory (ANT), which is built on Scientific Realism and Social Constructivism.

ANT assumes that a network is the topology (structure) of the environment and that actors are not always human. Connectivism puts greater emphasis on technology as both an actor and connector.

The process of clustering or sub-dividing a network depends on the number of connections between elements in the network.

Often clusters of sub-networks are still just nodes in a “real” network.

The impact of individual changes in a network are not always proportional to one another.

I’ll summarize additional concepts and key points as I read through the article.

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